From: Thomas Fröjd <tfrojd_at_gmail.com>

Date: Tue, 08 Jul 2008 17:41:30 +0200

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Tue 08 Jul 2008 - 15:45:12 GMT

Date: Tue, 08 Jul 2008 17:41:30 +0200

Hi thanks for your answer.

I belive this is what is confounding me. I have a bin width of 0.1 in the histogram. Changing

dens$y <- dens$y * (length(weights$Weight))

to

dens$y <- dens$y * (length(weights$Weight)*binwidth)

where binwidth=0.1 seems to output correct graphs.

Can someone verify this is the right approach?

On Tue, Jul 8, 2008 at 1:45 PM, S Ellison <S.Ellison_at_lgc.co.uk> wrote:

> Two thoughts:

*> i) If you have a narrow distribution, the density can be higher than 1. The area comes out at 1 for density, and n for the frequency.
**>
**> ii) hist() will not show the same frequencies as density() unless hist has unit bin sizes. density*length is showing number per unit change in Weight; hist shows number per bin width.
**>
**>
**>
**>
**>
**>
**> Try plotting a histogram first, then plot the density on top of that. If they disagree >>> "Thomas Fröjd" <tfrojd_at_gmail.com> 07/08/08 12:29 PM >>>
**> Hi!
**>
**> Sorry for bothering you again but I can't seem to get it right.
**>
**> When i multiply the density with the number of observations it seems
**> to be way to high, The reference curve is drawn at maybe 20 times
**> higher frequency count than it should be.
**>
**> I use the following code where "weights$Weight" is my weights data and
**> "reference" is my reference dataset.
**>
**> # calucate the right breakpoints
**> breakpoints <- seq(min(weights), max(weights), by=binwidth)
**>
**>
**> #scale density
**> dens <- density(reference)
**> dens$y <- dens$y * (length(weights$Weight))
**>
**> #graph it
**> hist(weights$Weight, freq=TRUE, breaks=breakpoints, main=wfiles[i])
**>
**> lines(dens)
**>
**> Any ideas are greatly appreciated.
**>
**> /Thomas
**>
**>
**>
**> On Fri, Jun 27, 2008 at 10:54 PM, Daniel Folkinshteyn
**> <dfolkins_at_gmail.com> wrote:
**>> if you want the "frequency" scale rather than density scale, then leave hist
**>> as is (by default it uses the frequency scale), and rescale the density by
**>> multiplying it by the appropriate NOBS.
**>>
**>> on 06/27/2008 01:16 PM Thomas Frööjd said the following:
**>>>
**>>> Hi
**>>>
**>>> Thank you very much for taking time to answer.
**>>>
**>>> The solution of using hist(data) for the main dataset and adding
**>>> lines(density(refdata)) for the reference data seem to work great. I
**>>> forgot to mention one thing however, I need to have frequency on the y
**>>> azis instead of density as now.
**>>>
**>>> I know this is not a "real" histogram but since the audience is not
**>>> very statistically experienced I would prefer to do it this way.
**>>> Anyone have an idea?
**>>>
**>>> Thanks again for your help.
**>>>
**>>> Thomas Fröjd
**>>>
**>>> On Wed, Jun 25, 2008 at 6:16 PM, Daniel Folkinshteyn <dfolkins_at_gmail.com>
**>>> wrote:
**>>>>>
**>>>>> I don't understand this. Why not just get hist() to plot on the
**>>>>> density scale,
**>>>>> thereby making its output commensurate with the output of density()?
**>>>>> The hist() function will plot on the density scale if you ask it to.
**>>>>> Set freq=FALSE
**>>>>> (or prob=TRUE) in the call to hist.
**>>>>
**>>>> ehrm... because i didn't realize that option existed :) that certainly is
**>>>> easier than manually scaling hist output by NOBS - thanks for the tip!
**>>>>
**>>>
**>>
**>>
**>
**> ______________________________________________
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**> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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**>
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